Paper
4 March 2013 3D interactive augmented reality-enhanced digital learning systems for mobile devices
Kai-Ten Feng, Po-Hsuan Tseng, Pei-Shuan Chiu, Jia-Lin Yang, Chun-Jie Chiu
Author Affiliations +
Proceedings Volume 8649, The Engineering Reality of Virtual Reality 2013; 864908 (2013) https://doi.org/10.1117/12.2003505
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
With enhanced processing capability of mobile platforms, augmented reality (AR) has been considered a promising technology for achieving enhanced user experiences (UX). Augmented reality is to impose virtual information, e.g., videos and images, onto a live-view digital display. UX on real-world environment via the display can be e ectively enhanced with the adoption of interactive AR technology. Enhancement on UX can be bene cial for digital learning systems. There are existing research works based on AR targeting for the design of e-learning systems. However, none of these work focuses on providing three-dimensional (3-D) object modeling for en- hanced UX based on interactive AR techniques. In this paper, the 3-D interactive augmented reality-enhanced learning (IARL) systems will be proposed to provide enhanced UX for digital learning. The proposed IARL systems consist of two major components, including the markerless pattern recognition (MPR) for 3-D models and velocity-based object tracking (VOT) algorithms. Realistic implementation of proposed IARL system is conducted on Android-based mobile platforms. UX on digital learning can be greatly improved with the adoption of proposed IARL systems.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kai-Ten Feng, Po-Hsuan Tseng, Pei-Shuan Chiu, Jia-Lin Yang, and Chun-Jie Chiu "3D interactive augmented reality-enhanced digital learning systems for mobile devices", Proc. SPIE 8649, The Engineering Reality of Virtual Reality 2013, 864908 (4 March 2013); https://doi.org/10.1117/12.2003505
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Cited by 2 scholarly publications.
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KEYWORDS
3D modeling

Detection and tracking algorithms

Skin

Pattern recognition

3D acquisition

Cameras

Databases

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